Institutional Review Board approval was obtained from the University of Nebraska Medical Center and Children's Hospital and Medical Center (Omaha, Nebraska) for this study. Children were assessed in the clinic using an interdisciplinary approach. After the 6-month visit, children were tracked to determine their acceptance rate into early intervention services. The clinic is staffed by a developmental/behavioral pediatrician, an occupational and a physical therapist, and a psychology graduate student at the postmasters level. In 2006, the clinic adopted the newly released BSID-III Screening Test. The BSID-III Screening Test has been found to have consistent results, with both high reliability and validity. High test-retest reliability was found across domains (r = 0.80–0.83). Studies with special groups supported the validity of the assessment with relatively low number of children who were developing typically classified as at risk for developmental delay, whereas a relatively high number of children from clinical groups known to be at risk for delay were classified appropriately.12 On the BSID-III Screening Test–GMS, the clinician identifies the appropriate subset of gross motor items to complete based on the child's chronological age. The child must successfully complete the first item of the subset of items to obtain a basal level and a ceiling is established by obtaining a zero on 4 consecutive items. Sample items include the following: (1) makes crawling movements, (2) elevates trunk while prone, (3) sits with support for 30 seconds, and (4) rolls from back to stomach. Typically a 6-month-old child would be observed on a range of 8 to 12 items.
On the BSID-III Screening Test, the child's performance is scored on the basis of a risk category classification: competent, emerging, or at risk. These risk categories were determined on the basis of comparison of scores with the BSID-III. Raw scores on both the BSID-III and BSID-III Screening Test are converted to age-corrected z scores in order to have a common measure. Table 3 describes the scaled score equivalent to the BSID-III and the definition for each classification. Although the Bayley-III Screening Test screens 4 areas (cognitive, language, fine, and gross motor) for purposes of this study, only the results of the GMS were used.
At the clinic visit as part of the gross motor evaluation the AIMS was also administered. The AIMS is used to identify infants with gross motor delay from birth to 18 months. It measures gross motor development from both a quantitative and a qualitative perspective. The AIMS is reported as a percentile rank on the basis of a raw score. The AIMS is considered a reliable and valid instrument for measuring infant motor development.11 The interrater reliability coefficient was high (r = 0.9891). Concurrent validity of the AIMS was reported for both the Bayley Scales of Infant Development GMS (r = 0.93) and the Peabody Development Motor Scale (r = 0.95) using a population of infants identified as normal and abnormal.11 In addition, the AIMS has been shown to have high levels of intrarater and interrater reliability and high concurrent validity when used with infants born preterm.11
SPSS statistical package version 16.0 was used to perform the data analyses. To answer the question about the relationship (ie, correlation) between the BSID-III Screening Test–GMS and the AIMS, the scaled scores of the BSID-III Screening Test–GMS were compared with the percentile scores of the AIMS using a point biserial correlation method. To answer the question about the best predictors of acceptance into early intervention services, a binary logical regression analysis was used. The predictor variables for this regression analysis included the scaled scores on the BSID-III Screening Test and the percentile scores on the AIMS. The criterion variable used for the analysis was acceptance of participants into early intervention services.
Both the BSID-III Screening Test and AIMS were completed on 93 children at their first Developmental TIPS clinic visit at 6 to 8 months' corrected age. The first analysis evaluated the relationship of the 2 gross motor assessments. The results of the point biserial correlation revealed that the BSID-III Screening Test–GMS and the AIMS had a weak to moderate correlation in this population (r = 0.397).
The second analysis evaluated to what degree the results of the 2 gross motor assessments predicted acceptance into early intervention. A total of 14% of the children (n = 13) were accepted for early intervention. Of those accepted for early intervention, 38.5% (n = 5) scored in the “at risk” range, 23.1% (n = 3) scored in the “emergent” range, and 38.5% (n = 5) scored in the “competent” range on the BSID-II Screening Test–GMS. Of those who did not receive early intervention (n = 80), both referred and not referred, 5% (n = 4) scored in the “at risk” range, 18.8% (n = 15) scored in the “emergent” range, and 76.2% (n = 61) scored in the “competent” range on the BSID-II Screening Test–GMS.
On the AIMS, children who were accepted for early intervention (n = 13) had a mean percentile score of 16% compared with those children (n = 80) who were not receiving service and who had a mean percentile score of 28.2%. The regression analysis revealed that the BSID-III Screening Test–GMS accounted for a significant portion of the variance in acceptance to early intervention services, χ2(1) = 7.871, P = .005. The BSID-III Screening Test–GMS was the only variable in the model that accounted for a significant portion of the acceptance category variance (Cox and Snell, R2 = 0.093; Nagelkerke, R2 = 0.165). The AIMS scores were excluded from the analysis as they did not provide additional variance to acceptance status beyond that provided by the BSID-III Screening Test–GMS.
Because of the increasing number of infants born preterm who are known to be at a greater risk for disability, there is a growing need by community health care providers to identify children at an early age that may benefit from early intervention services. The earlier this group of young infants can receive services, the more likely the effects of prematurity can potentially be ameliorated. This study confirmed previous research that suggests that delays for the young infants are typically in the motor area and highlights the need for an effective screening tool. The BSID-III Screening Test–GMS provides clinicians with a multiuse assessment that can either focus on a single domain or provide a comprehensive screening approach across domains. The results of this study suggest that, for the NICU population, the BSID-III Screening Test–GMS can effectively identify those young infants who need early intervention services. Most importantly, the test provides clinicians a time-efficient means for assessing young children.
As reported earlier, the BSID–III and the AIMS were highly correlated (r = 0.93). So it was surprising the BSID-III Screening Test–GMS and AIMS were not highly correlated (r = 0.397). One explanation may be that each assessment has a distinctly different purpose resulting in a difference in the type and function of the item set selected for each assessment. The Bayley-III Screening Test–GMS was developed to cast a broad net to ensure that children with possible delays are not missed. Therefore, the items on this assessment were selected that highly discriminate those children needing to be referred for further assessment from those who do not need services. In contrast, the AIMS usefulness is 2-fold: to provide information for diagnosis, and for program planning of intervention strategies. Items on the AIMS were selected to provide finer discrimination between motor behaviors in order to provide more detailed information that is useful for determining both a diagnosis and for program planning.
Haastert et al13 found that the early gross motor development profile of infants born preterm was different from typical gross motor development, with the population of premature infants scoring significantly lower compared with infants born at term across all age levels. These results suggested the need to adjust the norms when using the AIMS with infants born preterm to better detect infants with mild gross motor problems or learning difficulties. A future study could determine whether the correlation between the AIMS and the BSID-III Screening Test–GMS would be improved if the adjusted AIMS scores were used for this population of infants born preterm and if the adjusted AIMS scores would better predict acceptance into early intervention than the original AIMS scoring.
The pattern of at-risk status and acceptance was found in the majority of the infants. A small subgroup (5) of the infants scored “competent” on the GMS, yet was accepted for services. Initially this was a surprising finding; however, closer examination of this subgroup found that these children were accepted on the basis of health needs (failed hearing screen, gastrotube feedings, etc) and in those circumstances they would be accepted because of health impairments. This eligibility criterion allows the child to be accepted without demonstrating significant delays. These results suggest that it is important that both health and gross motor factors be considered in making referrals to early intervention services.
A second subgroup of interest was those infants with emerging or at-risk status who were not accepted for early intervention services. Access to services was not an issue as early intervention services for infants in this state are mandated within the state education system. Typically children who scored in the emerging range are not accepted into services as they are not demonstrating significant delays but may be referred for services on the basis of the recommendations of the clinician. Of interest are those children who were at high risk. It would be expected that a small number of the children at risk for developmental delay (in this study there were 4) would not be eligible for services since the BSID-III Screening Test–GMS is used to screen. Its purpose is to cast a broad net to ensure that children are not missed who may be eligible for services. Of interest was that at their 16-month visit, 2 of these children were within the emerging range for their motor skills but were at risk for developmental delay in language skills and were accepted for services. This pattern of delay over time suggests that those children demonstrating risk for motor skills should have high priority for follow-up assessment to monitor their need for services.
Overall, the BSID-III Screening Test–GMS was found to be an effective tool at 6 to 8 months' corrected age for identifying children who were eligible for early intervention. With minimal training, the BSID-III Screening Test can be administered by members of the health care or early intervention team from any discipline. This cost-effective approach has the additional advantage of allowing the practitioner to screen multiple areas in a brief period of time. This type of screening tool has great applicability for transdisciplinary/interdisciplinary teams as it allows for the use of one tool to identify whether further assessment is needed.
It is essential for community health care providers to have cost-effective, valid assessment tools to assist in making decisions regarding referral for early intervention. The BSID-III Screening Test–GMS is a valuable resource for these practitioners as it allows for (1) completion of a comprehensive, domain-specific screening assessment for evaluating children's development, (2) completion of the assessment in a shorter-time frame than comprehensive evaluations, and (3) practitioners with a variety of training and skills to complete the screening. For the population of infants born premature, the BSID-III Screening Test–GMS effectively helped to appropriately identify those children in need of services, maximizing the benefits to the child.
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Keywords:© 2012 Lippincott Williams & Wilkins, Inc.
early intervention; female; humans; male; motor skills; neuropsychological tests/standards; neuropsychological tests/statistics & numerical data; predictive value of tests; preschool child; preterm infant; risk factors; time factors